Associate Director/Director, Computational Test Development

• PhD in computational biology, bioinformatics, biostatistics, or a closely related quantitative field. Direct experience with advanced NGS modalities (e.g., cell-free DNA, ChIP-Seq, or epigenomic signal processing) is highly preferred. • 4–9 years of industry experience in regulated diagnostics, liquid biopsy, or IVD development, ideally within a fast-paced, cross-functional R&D environment. • Proven track record working under a formal Quality Management System (ISO 13485, 21 CFR Part 820). • Hands-on experience contributing to regulatory submissions (such as Pre-Subs, De Novo, or 510(k) tracks). Please describe your specific role and submission type in your cover letter or CV. • Solid grasp of analytical validation frameworks, including CLSI EP guidelines, FDA IVD/CDx guidance, and CAP/CLIA requirements. • Fluency in R and/or Python for robust statistical modeling, data analysis, and reproducible reporting. • Strong communication skills with a demonstrated ability to present and defend analytical validation strategies to internal leadership, scientific advisors, and regulatory stakeholders. • Startup mindset: You thrive when taking autonomous ownership of projects, remain adaptive under evolving information, and execute effectively in an entrepreneurial environment.
Analytical Validation & Regulatory Execution • Design and develop computational approaches for characterizing the performance of existing and new epigenomic tests. • Define and implement metrics and analyses to assess NGS and epigenomic data quality to enable coordinated optimization of assay and diagnostic performance. • Lead the computational execution of verification and validation protocols, statistical analysis plans (SAPs), and performance summary reports to meet FDA evidentiary standards. • Translate complex computational results into clear, well-organized regulatory documentation for FDA submissions. • Stay current on FDA guidance for IVDs, companion diagnostics, and evolving LDT oversight to actively inform study design decisions. Statistical & Bioinformatics Analysis • Develop and apply statistical methods for diagnostic characterization, including LOD/LOQ, reproducibility, thresholding, gaurdbanding, and clinical utility endpoints. • Support and optimize robust, reproducible analysis pipelines—ensuring code traceability and standardization from raw NGS data through regulatory-grade outputs. • Identify and systematically address sources of variability, bias, and technical confounding across the computational workflow. Cross-Functional Collaboration • Partner closely with laboratory development, clinical operations, and regulatory affairs to ensure absolute scientific and regulatory alignment across programs. • Contribute to clinical study design—including sample size calculations, endpoint selection, and pre-specified SAPs using data-driven insights from analytical validation pilots.